SoroushVahidi/scidocs huggingface dataset:
Syntax and semantics in the acquisition of locative verbs.
(1991)

Children between the ages of three and seven occasionally make errors with locative verbs like pour and fill, such as *I filled water into the glass and *I poured the glass with water (Bowerman, 1982). To account for this pattern of errors, and for how they are eventually unlearned, we propose that children use a universal linking rule called object affectedness: the direct object corresponds to the argument that is specified as 'affected' in some particular way in the semantic representation of a verb. However, children must learn which verbs specify which of their arguments as being affected; specifically, whether it is the argument whose referent is undergoing a change of location, such as the content argument of pour, or the argument whose referent is undergoing a change of state, such as the container argument of fill. This predicts that syntactic errors should be associated with specific kinds of misinterpretations of verb meaning. Two experiments were performed on the ability of children and adults to understand and produce locative verbs. The results confirm that children tend to make syntactic errors with sentences containing fill and empty, encoding the content argument as direct object (e.g. fill the water). As predicted, children also misinterpreted the meanings of fill and empty as requiring not only that the container be brought into a full or empty state, but also that the content move in some specific manner (by pouring, or by dumping). Furthermore, children who misinterpreted the verbs' meanings were more likely to make syntactic errors with them. These findings support the hypothesis that verb meaning and syntax are linked in precise ways in the lexicons of language learners.
Dermal and subdermal tissue filling with fetal connective tissue and cartilage, collagen, and silicone: Experimental study in the pig compared with clinical results. A new technique of dermis mini-autograft injections
(1990)

The early reaction to the injection of silicone, collagen, and lyophilized heterologous fetal connective and cartilage tissues into the limiting zone deep dermis-superficial subcutaneous tissue was histologically examined in the pig and compared with clinical results. The inflammatory reaction to lyophilized heterologous fetal tissue is considerably more intense than that to collagen and silicone and lasts for several weeks. Therefore, it is not recommended for soft tissue filling in the face. Admitting an inferior antigenicity of fetal tissues, the authors suggest that enzymatically denaturalized collagen should be manufactured from heterologous fetal connective tissue, to be then further tested. The reaction of tissue to silicone and collagen is minimal. Silicone is preferred for dermal injections since in clinical experience it remains in the site of injection much longer. For subdermal injections, however, collagen is preferred. Based on experience with over 600 patients since 1958, the first author continues using liquid silicone. The lack of complications is probably a result of the fact that only small amounts (milliliters) of silicone were used in wrinkles or small depressions in the dermal layer and that from the beginning injection into the subcutaneous tissue was avoided. Since 1988 a new technique for the treatment of wrinkles and skin depressions with injections of dermal miniautografts has been used with satisfactory results.
Multi-modal Attention Mechanisms in LSTM and Its Application to Acoustic Scene Classification
(2018)

Neural network architectures such as long short-term memory (LSTM) have been proven to be powerful models for processing sequences including text, audio and video. On the basis of vanilla LSTM, multi-modal attention mechanisms are proposed in this paper to synthesize the time and semantic information of input sequences. First, we reconstruct the forget and input gates of the LSTM unit from the perspective of attention model in the temporal dimension. Then the memory content of the LSTM unit is recalculated using a cluster-based attention mechanism in semantic space. Experiments on acoustic scene classification tasks show performance improvements of the proposed methods when compared with vanilla LSTM. The classification errors on LITIS ROUEN dataset and DCASE2016 dataset are reduced by 16.5% and 7.7% relatively. We get a second place in the Kaggle’s YouTube-8M video understanding challenge, and multi-modal attention based LSTM model is one of our bestperforming single systems.
The regulation of explicit and implicit race bias: the role of motivations to respond without prejudice.
(2002)

Three studies examined the moderating role of motivations to respond without prejudice (e.g., internal and external) in expressions of explicit and implicit race bias. In all studies, participants reported their explicit attitudes toward Blacks. Implicit measures consisted of a sequential priming task (Study 1) and the Implicit Association Test (Studies 2 and 3). Study 3 used a cognitive busyness manipulation to preclude effects of controlled processing on implicit responses. In each study, explicit race bias was moderated by internal motivation to respond without prejudice, whereas implicit race bias was moderated by the interaction of internal and external motivation to respond without prejudice. Specifically, high internal, low external participants exhibited lower levels of implicit race bias than did all other participants. Implications for the development of effective self-regulation of race bias are discussed.
If Only my Leader Would just Do Something! Passive Leadership Undermines Employee Well-being Through Role Stressors and Psychological Resource Depletion.
(2017)

The goal of this study was to develop and test a sequential mediational model explaining the negative relationship of passive leadership to employee well-being. Based on role stress theory, we posit that passive leadership will predict higher levels of role ambiguity, role conflict and role overload. Invoking Conservation of Resources theory, we further hypothesize that these role stressors will indirectly and negatively influence two aspects of employee well-being, namely overall mental health and overall work attitude, through psychological work fatigue. Using a probability sample of 2467 US workers, structural equation modelling supported the model by showing that role stressors and psychological work fatigue partially mediated the negative relationship between passive leadership and both aspects of employee well-being. The hypothesized, sequential indirect relationships explained 47.9% of the overall relationship between passive leadership and mental health and 26.6% of the overall relationship between passive leadership and overall work attitude. Copyright © 2016 John Wiley & Sons, Ltd.
The Timeboxing process model for iterative software development
(2004)

In today’s business where speed is of essence, an iterative development approach that allows the functionality to be delivered in parts has become a necessity and an effective way to manage risks. In an iterative process, the development of a software system is done in increments, each increment forming of an iteration and resulting in a working system. A common iterative approach is to decide what should be developed in an iteration and then plan the iteration accordingly. A somewhat different iterative is approach is to time box different iterations. In this approach, the length of an iteration is fixed and what should be developed in an iteration is adjusted to fit the time box. Generally, the time boxed iterations are executed in sequence, with some overlap where feasible. In this paper we propose the timeboxing process model that takes the concept of time boxed iterations further by adding pipelining concepts to it for permitting overlapped execution of different iterations. In the timeboxing process model, each time boxed iteration is divided into equal length stages, each stage having a defined function and resulting in a clear work product that is handed over to the next stage. With this division into stages, pipelining concepts are employed to have multiple time boxes executing concurrently, leading to a reduction in the delivery time for product releases. We illustrate the use of this process model through an example of a commercial project that was successfully executed using the proposed model.
Iterative and incremental developments. a brief history
(2003)

Although many view iterative and incremental development as a modern practice, its application dates as far back as the mid-1950s. Prominent software-engineering thought leaders from each succeeding decade supported IID practices, and many large projects used them successfully. These practices may have differed in their details, but all had a common theme-to avoid a single-pass sequential, document-driven, gated-step approach.
A Methodology for Collecting Valid Software Engineering Data
(1984)

An effective data collection method for evaluating software development methodologies and for studying the software development process is described. The method uses goal-directed data collection to evaluate methodologies with respect to the claims made for them. Such claims are used as a basis for defining the goals of the data collection, establishing a list of questions of interest to be answered by data analysis, defining a set of data categorization schemes, and designing a data collection form. The data to be collected are based on the changes made to the software during development, and are obtained when the changes are made. To ensure accuracy of the data, validation is performed concurrently with software development and data collection. Validation is based on interviews with those people supplying the data. Results from using the methodology show that data validation is a necessary part of change data collection. Without it, as much as 50 percent of the data may be erroneous. Feasibility of the data collection methodology was demonstrated by applying it to five different projects in two different environments. The application showed that the methodology was both feasible and useful.
Quantitative Evaluation of Software Quality
(1976)

The study reported in this paper establishes a conceptual framework and some key initial results in the analysis of the characteristics of software quality. Its main results and conclusions are:
 • Explicit attention to characteristics of software quality can lead to significant savings in software life-cycle costs.
 • The current software state-of-the-art imposes specific limitations on our ability to automatically and quantitatively evaluate the quality of software.
 • A definitive hierarchy of well-defined, well-differentiated characteristics of software quality is developed. Its higher-level structure reflects the actual uses to which software quality evaluation would be put; its lower-level characteristics are closely correlated with actual software metric evaluations which can be performed.
 • A large number of software quality-evaluation metrics have been defined, classified, and evaluated with respect to their potential benefits, quantifiability, and ease of automation.
 •Particular software life-cycle activities have been identified which have significant leverage on software quality.
 Most importantly, we believe that the study reported in this paper provides for the first time a clear, well-defined framework for assessing the often slippery issues associated with software quality, via the consistent and mutually supportive sets of definitions, distinctions, guidelines, and experiences cited. This framework is certainly not complete, but it has been brought to a point sufficient to serve as a viable basis for future refinements and extensions.
A tutorial on the dynamics and control of wind turbines and wind farms
(2009)

Wind energy is currently the fastest-growing energy source in the world, with a concurrent growth in demand for the expertise of engineers and researchers in the wind energy field. There are still many unsolved challenges in expanding wind power, and there are numerous problems of interest to systems and control researchers. In this paper, we first review the basic structure of wind turbines and then describe wind turbine control systems and control loops. Of great interest are the generator torque and blade pitch control systems, where significant performance improvements are achievable with more advanced systems and control research. We describe recent developments in advanced controllers for wind turbines and wind farms, and we also outline many open problems in the areas of modeling and control of wind turbines.
ReLiDSS: Novel lie detection system from speech signal
(2016)

Lying is among the most common wrong human acts that merits spending time thinking about it. The lie detection is until now posing a problem in recent research which aims to develop a non-contact application in order to estimate physiological changes. In this paper, we have proposed a preliminary investigation on which relevant acoustic parameter can be useful to classify lie or truth from speech signal. Our proposed system in is based on the Mel Frequency Cepstral Coefficient (MFCC) commonly used in automatic speech processing on our own constructed database ReLiDDB (ReGIM-Lab Lie Detection DataBase) for both cases lie detection and person voice recognition. We have performed on this database the Support Vector Machines (SVM) classifier using Linear kernel and we have obtained an accuracy of Lie and Truth detection of speech audio respectively 88.23% and 84.52%.
On Software Implementation of High Performance GHASH Algorithms
(2012)

There have been several modes of operations available for symmetric key block ciphers, among which Galois Counter Mode (GCM) of operation is a standard. GCM mode of operation provides con dentiality with the help of symmetric key block cipher operating in counter mode. The authentication component of GCM comprises of Galois hash (GHASH) computation which is a keyed hash function. The most important component of GHASH computation is carry-less multiplication of 128bit operands which is followed by a modulo reduction. There have been a number of schemes proposed for e cient software implementation of carry-less multiplication to improve performance of GHASH by increasing the speed of multiplications. This thesis focuses on providing an e cient way of software implementation of high performance GHASH function as being proposed by Meloni et al., and also on the implementation of GHASH using a carry-less multiplication instruction provided by Intel on their Westmere architecture. The thesis work includes implementation of the high performance GHASH and its comparison to the older or standard implementation of GHASH function. It also includes comparison of the two implementations using Intel's carry-less multiplication instruction. This is the rst time that this kind of comparison is being done on software implementations of these algorithms. Our software implementations suggest that the new GHASH algorithm, which was originally proposed for the hardware implementations due to the required parallelization, can't take advantage of the Intel carry-less multiplication instruction PCLMULQDQ. On the other hand, when implementations are done without using the PCLMULQDQ instruction the new algorithm performs better, even if its inherent parallelization is not utilized. This suggest that the new algorithm will perform better on embedded systems that do not support PCLMULQDQ.
Theory of Credit Card Networks : A Survey of the Literature
(2003)

Credit cards provide benefits to consumers and merchants not provided by other payment instruments as evidenced by their explosive growth in the number and value of transactions over the last 20 years. Recently, credit card networks have come under scrutiny from regulators and antitrust authorities around the world. The costs and benefits of credit cards to network participants are discussed. Focusing on interrelated bilateral transactions, several theoretical models have been constructed to study the implications of several business practices of credit card networks. The results and implications of these economic models along with future research topics are discussed.
Cytoscape.js: a graph theory library for visualisation and analysis
(2015)

UNLABELLED
Cytoscape.js is an open-source JavaScript-based graph library. Its most common use case is as a visualization software component, so it can be used to render interactive graphs in a web browser. It also can be used in a headless manner, useful for graph operations on a server, such as Node.js.


AVAILABILITY AND IMPLEMENTATION
Cytoscape.js is implemented in JavaScript. Documentation, downloads and source code are available at http://js.cytoscape.org.


CONTACT
gary.bader@utoronto.ca.
Time series forecasting using a deep belief network with restricted Boltzmann machines
(2014)

Multi-layer perceptron (MLP) and other artificial neural networks (ANNs) have been widely applied to time series forecasting since 1980s. However, for some problems such as initialization and local optima existing in applications, the improvement of ANNs is, and still will be the most interesting study for not only time series forecasting but also other intelligent computing fields. In this study, we propose a method for time series prediction using Hinton & Salakhutdinov’s deep belief nets (DBN) which are probabilistic generative neural network composed by multiple layers of restricted Boltzmann machine (RBM). We use a 3-layer deep network of RBMs to capture the feature of input space of time series data, and after pretraining of RBMs using their energy functions, gradient descent training, i.e., back-propagation learning algorithm is used for fine-tuning connection weights between “visible layers” and “hidden layers” of RBMs. To decide the sizes of neural networks and the learning rates, Kennedy & Eberhart’s particle swarm optimization (PSO) is adopted during the training processes. Furthermore, “trend removal”, a preprocessing to the original data, is also approached in the forecasting experiment using CATS benchmark data. Additionally, approximating and short-term prediction of chaotic time series such as Lorenz chaos and logistic map were also applied by the proposed method.
Hierarchical structure and the prediction of missing links in networks
(2008)

Networks have in recent years emerged as an invaluable tool for describing and quantifying complex systems in many branches of science. Recent studies suggest that networks often exhibit hierarchical organization, in which vertices divide into groups that further subdivide into groups of groups, and so forth over multiple scales. In many cases the groups are found to correspond to known functional units, such as ecological niches in food webs, modules in biochemical networks (protein interaction networks, metabolic networks or genetic regulatory networks) or communities in social networks. Here we present a general technique for inferring hierarchical structure from network data and show that the existence of hierarchy can simultaneously explain and quantitatively reproduce many commonly observed topological properties of networks, such as right-skewed degree distributions, high clustering coefficients and short path lengths. We further show that knowledge of hierarchical structure can be used to predict missing connections in partly known networks with high accuracy, and for more general network structures than competing techniques. Taken together, our results suggest that hierarchy is a central organizing principle of complex networks, capable of offering insight into many network phenomena.
PROPOSED METHODOLOGY FOR EARTHQUAKE-INDUCED LOSS ASSESSMENT OF INSTRUMENTED STEEL FRAME BUILDINGS : BUILDING-SPECIFIC AND CITY-SCALE APPROACHES
(2017)

The performance-based earthquake engineering framework utilizes probabilistic seismic demand models to obtain accurate estimates of building engineering demand parameters. These parameters are utilized to estimate earthquake-induced losses in terms of probabilistic repair costs, life-safety impact, and loss of function due to damage to a wide variety of building structural and non-structural components and content. Although nonlinear response history analysis is a reliable tool to develop probabilistic seismic demand models, it typically requires a considerable time investment in developing detailed building numerical model representations. In that respect, the challenge of city-scale damage assessment still remains. This paper proposes a simplified methodology that rapidly assesses the story-based engineering demand parameters (e.g., peak story drift ratios, residual story drift ratios, peak absolute floor accelerations) along the height of a steel frame building in the aftermath of an earthquake. The proposed methodology can be employed at a city-scale in order to facilitate rapid earthquake-induced loss assessment of steel frame buildings in terms of structural damage and monetary losses within a region. Therefore, buildings within an urban area that are potentially damaged after an earthquake event or scenario can be easily identified without a detailed engineering inspection. To illustrate the methodology for rapid earthquake-induced loss assessment at the city-scale we employ data from instrumented steel frame buildings in urban California that experienced the 1994 Northridge earthquake. Maps that highlight the expected structural and nonstructural damage as well as the expected earthquake-induced monetary losses are developed. The maps are developed with the geographical information system for steel frame buildings located in Los Angeles. Seong-Hoon Hwang and Dimitrios G. Lignos
Forecasting the winner of a tennis match
(2003)

We propose a method to forecast the winner of a tennis match, not only at the beginning of the match, but also (and in particular) during the match. The method is based on a fast and flexible computer program, and on a statistical analysis of a large data set from Wimbledon, both at match and at point level. 2002 Elsevier Science B.V. All rights reserved.
Overconfidence in IT Investment Decisions: Why Knowledge can be a Boon and Bane at the same Time
(2011)

Despite their strategic relevance in organizations, information technology (IT) investments still result in alarmingly high failure rates. As IT investments are such a delicate high-risk/high-reward matter, it is crucial for organizations to avoid flawed IT investment decision-making. Previous research in consumer and organizational decision-making shows that a decision’s accuracy is often influenced by decisionmakers’ overconfidence and that the magnitude of overconfidence strongly depends on decision-makers’ certainty of their knowledge. Drawing on these strands of research, our findings from a field survey (N=166) show that IT managers’ decisions in IT outsourcing are indeed affected by overconfidence. However, an in-depth investigation of three types of knowledge, namely experienced, objective and subjective knowledge, reveals that different types of knowledge can have contrasting effects on overconfidence and thus on the quality of IT outsourcing decisions. Knowledge can be a boon and bane at the same time. Implications for research and practice are discussed.